Ultraviolet solar flare signatures in the framework of complex network

Area of Science:

• Solar Physics
• Complex Systems Science
• Network Science

Background:

• Natural phenomena, like solar flares, exhibit complex behaviors difficult to analyze with traditional methods.
• The complex network approach offers a way to quantify time-evolving structures and understand system interactions.

Purpose of the Study:

• To apply an unsupervised network-based method to identify solar flare positions and occurrence times.
• To investigate variations in network parameters across different solar regions (flaring, non-flaring active, and quiet-Sun) during flaring and non-flaring phases.

Main Methods:

• Utilized ultraviolet emission data (1600 Å) from the Solar Dynamics Observatory's Atmospheric Imaging Assembly.
• Constructed networks by partitioning datasets into sub-windows and calculating Pearson correlations between time series and intensities.
• Analyzed network parameters including clustering coefficient, degree centrality, characteristic length, and PageRank.

Main Results:

• Solar flare triggering significantly influences network parameters near the flare's occurrence time and location.
• During the flaring phase, the clustering coefficient and characteristic length approach values typical of a random network.
• Network parameter variations provide a signature associated with solar flare activity.

Conclusions:

• The study demonstrates the effectiveness of complex network analysis in characterizing solar flare dynamics.
• Findings suggest that network parameters derived from ultraviolet data can aid in detecting solar flare occurrence times and locations.